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Course materials and notes for Stanford class CS231n: Deep Learning for Computer Vision.

Torch CUDA Neural Network Implementation.

Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation.

Very simple implementation of neural networks for dummies in python without using any libraries, with detailed comments.

A PyTorch implementation of CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation".

Deeplearn-rs provides simple networks that use matrix multiplication, addition, and ReLU under the MIT license.

Deep learning in Rust, with shape checked tensors and neural networks.

Making neural nets uncool again, focused on making deep learning more accessible.

FeatherCNN is a high performance inference engine for convolutional neural networks.

Documentation - Financial Data API.

Deep Neural Networks for Golang (powered by MXNet).

Free AI writing and agent tools: Text Auditor, Humanizer, CLAUDE.md Writer, SKILL.md Generator, AI Writing Coach, and more. No account required.

Implementation of image to image (pix2pix) translation from the paper by isola et al.[DEEP LEARNING].

An unsupervised machine learning extension library for NetworkX with a Scikit-Learn like API.

A beginner-friendly guide on using Keras to implement a simple Neural Network in Python.

Simple API for Neural Network. Better for image processing with CPU/GPU + Transfer Learning.

Lightweight library to build and train neural networks in Theano.

Neural network inference from the command line, implemented in CHICKEN Scheme.

A graph sampling extension library for NetworkX with a Scikit-Learn like API.

A header-only C++11 Neural Network library. Low dependency, native traditional chinese document.

Collection of infrastructure and tools for research in neural network interpretability.

Implementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch.

A low-code framework for building custom AI models like LLMs and other deep neural networks. opensource.

Neural networks (boltzmann machines, feed-forward and recurrent nets), Gaussian Processes.